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In addition to the exhibition, collection, research, and educational functions of the museum, the development of a future museum includes the trend of leisure and sightseeing. Although the museum is a non-profit organization, if it can provide digital exhibits and collections under the premises of “intellectual property rights” and “cultural assets protection”, and licensing and adding value in various fields, it can generate revenue from digital licensing and handle the expenses of museum operations. This will be a new trend in the sustainable development of museum operations. Especially since the outbreak of COVID-19 at the beginning of this year (2020), the American Alliance of Museums (AAM) recently stated that nearly a third of the museums in the United States may be permanently closed since museum operations are facing “extreme financial difficulties.” This research is aimed at museums using the business model of “digital authorization”. It proposes an authorization mechanism based on blockchain technology protecting the museums’ digital rights in the business model and the application of cryptography. The signature and time stamp mechanism achieve non-repudiation and timeless mechanism, which combines blockchain and smart contracts to achieve verifiability, un-forgery, decentralization, and traceability, as well as the non-repudiation of the issue of cash flow with signatures and digital certificates, for the digital rights of museums in business. The business model proposes achievable sustainable development. Museums not only achieve the goal of promoting social education, but also solve their financial problems.

Novel computing paradigms, e.g., the Cloud, introduce new requirements with regard to access control such as utilization of historical information and continuity of decision. However, these concepts may introduce an additional level of complexity to the underpinning model, rendering its definition and verification a cumbersome and prone to errors process. Using a formal language to specify a model and formally verify it may lead to a rigorous definition of the interactions amongst its components, and the provision of formal guarantees for its correctness. In this paper, we consider a case study where we specify a formal model in TLA + for both a policy-neutral and policy-specific UseCON usage control model. Through that, we anticipate to shed light in the analysis and verification of usage control models and policies by sharing our experience when using TLA + specific tools.

XML is rapidly emerging as a standard for data representation and exchange over the World Wide Web and an increasing amount of sensitive business data is processed in XML format. Therefore, it is critical to have control mechanisms to restrict a user to access only the parts of XML documents that she is authorized to access. In this paper, we propose the first DTD-based access control model that employs graph matching to analyze if an input query is fully acceptable, fully rejectable, or partially acceptable. In this way, there will be no further security overhead for the processing of fully acceptable and rejectable queries. For partially acceptable queries, we propose a graph-matching based authorization model for an optimized rewriting procedure in which a recursive query (query with descendant axis ‘//’) will be rewritten into an equivalent recursive one if possible and into a non-recursive one only if necessary, resulting queries that can fully take advantage of structural join based query optimization techniques. Moreover, we propose an index structure for XML element types to speed up the query rewriting procedure, a facility that is potentially useful for applications with large DTDs. Our performance study results showed that our algorithms armed with rewriting indexes are promising.

Cookies represent an important element of HTTP providing state management to an otherwise stateless protocol. HTTP cookies currently in use are governed by the same origin policy that directs Web browsers to allow cookie sharing only between Web sites in the same DNS domain. As Web applications get richer, data sharing across domain boundaries becomes more important. While practical solutions to cross-domain data sharing exist, in many cases they increase complexity and cost. In this paper we propose a simple mechanism to share cookies using authorizations based on X.509 attribute and public key certificates. In addition to supporting secure cookie sharing between unrelated domains, it can be beneficial for hosts in the same domain when the currently used same origin policy is deemed too permissive, exposing cookies to leakage and spoofing.

This commentary discusses the current prior authorization (PA) process and the negative impacts it can have on patient care. According to the American Medical Association, 94% of patients experience delays in care and 78% abandon treatment altogether. These delays in care are often for lifesaving treatments and can result in adverse events. Additionally, PAs place an extensive administrative and financial burden on both patients and providers, often requiring several hours of seeking approval from insurance companies or requiring patients to try one or more other therapeutic avenues before an insurance company will approve the original course of treatment. This is all while insurance companies are making record profits each year. Frustrations with this system are leading to a rise in the number of physician practices switching to a cash-only business model, which increases autonomy, enables price transparency, and benefits both physicians and patients.

The U.S. COVID-19 vaccination program, which commenced in December 2020, has been instrumental in preventing morbidity and mortality from COVID-19 disease. Safety monitoring has been an essential component of the program. The federal government undertook a comprehensive and coordinated approach to implement complementary safety monitoring systems and to communicate findings in a timely and transparent way to healthcare providers, policymakers, and the public. Monitoring involved both well-established and newly developed systems that relied on both spontaneous (passive) and active surveillance methods. Clinical consultation for individual cases of adverse events following vaccination was performed, and monitoring of special populations, such as pregnant persons, was conducted. This report describes the U.S. government’s COVID-19 vaccine safety monitoring systems and programs used by the Centers for Disease Control and Prevention, the U.S. Food and Drug Administration, the Department of Defense, the Department of Veterans Affairs, and the Indian Health Service. Using the adverse event of myocarditis following mRNA COVID-19 vaccination as a model, we demonstrate how the multiple, complementary monitoring systems worked to rapidly detect, assess, and verify a vaccine safety signal. In addition, longer-term follow-up was conducted to evaluate the recovery status of myocarditis cases following vaccination. Finally, the process for timely and transparent communication and dissemination of COVID-19 vaccine safety data is described, highlighting the responsiveness and robustness of the U.S. vaccine safety monitoring infrastructure during the national COVID-19 vaccination program.

Purpose>Authorization and access control have been a topic of research for several decades. However, existing definitions are inconsistent and even contradicting each other. Furthermore, there are numerous access control models and even more have recently evolved to conform with the challenging requirements of resource protection. That makes it hard to classify the models and decide for an appropriate one satisfying security needs. Therefore, this study aims to guide through the plenty of access control models in the current state of the art besides this opaque accumulation of terms meaning and how they are related.Design/methodology/approach>This study follows the systematic literature review approach to investigate current research regarding access control models and illustrate the findings of the conducted review. To provide a detailed understanding of the topic, this study identified the need for an additional study on the terms related to the domain of authorization and access control.Findings>The authors’ research results in this paper are the distinction between authorization and access control with respect to definition, strategies, and models in addition to the classification schema. This study provides a comprehensive overview of existing models and an analysis according to the proposed five classes of access control models.Originality/value>Based on the authors’ definitions of authorization and access control along with their related terms, i.e. authorization strategy, model and policy as well as access control model and mechanism, this study gives an overview of authorization strategies and propose a classification of access control models providing examples for each category. In contrast to other comparative studies, this study discusses more access control models, including the conventional state-of-the-art models and novel ones. This study also summarizes each of the literature works after selecting the relevant ones focusing on the database system domain or providing a survey, a classification or evaluation criteria of access control models. Additionally, the introduced categories of models are analyzed with respect to various criteria that are partly selected from the standard access control system evaluation metrics by the National Institute of Standards and Technology.

This paper explores the labor market and schooling effects of the Deferred Action for Childhood Arrivals (DACA) initiative, which provides work authorization to eligible immigrants along with a temporary reprieve from deportation. The analysis relies on a difference-in-differences approach which exploits the discontinuity in program rules to compare eligible individuals to ineligible, likely undocumented immigrants before and after the program went into effect. To address potential endogeneity concerns, we focus on youths that likely met DACA’s schooling requirement when the program was announced. We find that DACA reduced the probability of school enrollment of eligible higher-educated individuals, as well as some evidence that it increased the employment likelihood of men, in particular. Together, these findings suggest that a lack of authorization may lead individuals to enroll in school when working is not a viable option. Thus, once employment restrictions are relaxed and the opportunity costs of higher education rise, eligible individuals may reduce investments in schooling.

At the end of 2023, Bayer AG launched its own internal large language model (LLM), MyGenAssist, based on ChatGPT technology to overcome data privacy concerns. It may offer the possibility to decrease their harshness and save time spent on repetitive and recurrent tasks that could then be dedicated to activities with higher added value. Although there is a current worldwide reflection on whether artificial intelligence should be integrated into pharmacovigilance, medical literature does not provide enough data concerning LLMs and their daily applications in such a setting. Here, we studied how this tool could improve the case documentation process, which is a duty for authorization holders as per European and French good vigilance practices. The aim of the study is to test whether the use of an LLM could improve the pharmacovigilance documentation process. MyGenAssist was trained to draft templates for case documentation letters meant to be sent to the reporters. Information provided within the template changes depending on the case: such data come from a table sent to the LLM. We then measured the time spent on each case for a period of 4 months (2 months before using the tool and 2 months after its implementation). A multiple linear regression model was created with the time spent on each case as the explained variable, and all parameters that could influence this time were included as explanatory variables (use of MyGenAssist, type of recipient, number of questions, and user). To test if the use of this tool impacts the process, we compared the recipients' response rates with and without the use of MyGenAssist. An average of 23.3% (95% CI 13.8%-32.8%) of time saving was made thanks to MyGenAssist (P<.001; adjusted R =0.286) on each case, which could represent an average of 10.7 (SD 3.6) working days saved each year. The answer rate was not modified by the use of MyGenAssist (20/48, 42% vs 27/74, 36%; P=.57) whether the recipient was a physician or a patient. No significant difference was found regarding the time spent by the recipient to answer (mean 2.20, SD 3.27 days vs mean 2.65, SD 3.30 days after the last attempt of contact; P=.64). The implementation of MyGenAssist for this activity only required a 2-hour training session for the pharmacovigilance team. Our study is the first to show that a ChatGPT-based tool can improve the efficiency of a good practice activity without needing a long training session for the affected workforce. These first encouraging results could be an incentive for the implementation of LLMs in other processes.

PurposeThis paper aims to establish the determinants of production in the Spanish Designation of Origin (DO) area for Cava wine and forecasts sales to establish vineyard area variations that maintain market equilibrium.Design/methodology/approachBy applying a vector autoregressive (VAR) model, the authors forecast demand and the consequent requirements for base wine production.FindingsThe results show that Cava sales determine the base wine supply. After forecasting demand and the consequent requirements for base wine, the authors’ results show that, to avoid oversupply, the vineyard area for Cava wine should not be increased.Practical implicationsThe paper develops a simple and effective method for DOs affected by the current European wine plantation regulations to forecast from a supply and demand perspective and their surface needs in response to market changes.Originality/valueThis study contributes to the literature because, to the best of the authors’ knowledge, no other study has investigated the determinants of Cava supply and demand or defines a model to assess the effects of changes in growing areas. The model is applicable to other European protected designations of origin wines and would help policymakers to accurately establish vine planting authorizations.